Development of equity, diversity, and inclusion competencies in residents and faculty in oncology through formal and informal learning.
Notice bibliographique
Résumé
9053 Background: In recent years, a growing body of literature has suggested that patients need their clinicians to provide culturally competent care. A focus on integrated and longitudinal training within the domains of equity, diversity and inclusion (EDI) is needed to equip physicians to meet patients’ needs. Oncology is one such specialty that needs strong skillsets in EDI given its vulnerable and complex patient populations. This study explores how physicians within oncology learn about the domains of EDI through formal and informal learning. Methods: Using constructivist grounded theory (CGT), this study explores EDI competency formation at one academic center – the Juravinski Cancer Center in Hamilton ON, Canada. A purposive sample of 16 staff and resident physicians was taken to incorporate variation sampling - including a variety of ages, genders, and work/training experience. Participants were from both medical and radiation oncology. Semi-structured one-on-one interviews were conducted. Transcripts were generated, anonymized, and analyzed iteratively. Data analysis followed stages of open, axial, and selective coding through which themes were constructed. Interviews were continued until data saturation was reached. Results: Of the 16 participants, there was an even distribution between men (8) and women (8). Mean age was 43 (range 30-65). There were 5 residents and 11 faculty members. 9 were from medical oncology and 7 from radiation oncology. The major themes generated from the study were: the relationship between EDI competencies and professional identify formation, the role of culture and context in influencing exposure and learning about EDI, and the relationship between formal and informal learning opportunities. Conclusions: This study is the first to explore of how oncologists presently develop EDI competencies through formal and informal learning. The study has discovered the role of professional identify formation as a factor influencing learning, the impact of the culture and context of medicine, and the significant interplay between formal and informal learning in developing EDI skillsets. While much learning takes place informally, informed by clinical encounters and personal experiences, there is a need to marry the informal learning opportunities to more structured formal teaching in the training and clinical environment. [Table: see text]
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».